Incorporating Uncertain and Incomplete Subjective Judgments into the Evaluation Procedure of Transportation Demand Management Alternatives

This paper proposes a methodology for evaluating transportation demand management (TDM) alternatives in the context of multi-criteria decision making (MCDM). The proposed approach takes into account not only quantitative criteria (i.e. transportation and environmental impacts) but also qualitative criteria (i.e. social impacts) which are intrinsically uncertain and subjective. The transportation impacts of the TDM alternatives are estimated by TRIPS¹ program, while the MOBILE5a² is employed in order to estimate environmental impacts in terms of NO_X, CO and Hydrocarbon. The social impacts of the TDM alternatives are estimated by interviewing relevant experts. Consequently, the uncertain subjective judgements were quantified by the evidential reasoning (ER) approach based on decision theory and Dempster–Shafer theory of evidence. In order to measure the weights of criteria, analytical hierarchy process (AHP) is adopted. As a last step, the CODASID³ method based on a complete concordance and discordance analysis is used to rank alternative TDM schemes. The proposed approach is demonstrated by ranking 14 TDM alternatives, which are chosen for the central business area in Bangkok, Thailand of 22-square-kilometers.     

综合运输基本公共服务评价方法研究

为指导交通运输管理部门开展综合运输基本公共服务水平评价,本文在充分调研我国县域综合运输基本公共服务现状的基础上,提出了我国综合运输基本公共服务的基本概念和内涵特征,明确提出了我国开展综合运输基本公共服务评价的必要性、范围、基本原则等总体思路。在此基础上,提出了我国综合运输基本公共服务的具体评价方法、评价流程、评价结果应用、评价组织、具体指标计算等内容。最后以宁夏西吉县为例,验证了评价方法的可行性,为我国科学开展综合运输基本公共服务评价提供了重要的决策支撑。研究表明,综合运输基本公共服务评价非常有必要,范围应当包括城市公交、农村客运、农村公路和邮政普遍服务四个方面,应当遵循发展性、激励性、客观性、可操作性、突出重点五大原则,评价指标体系应当包括四大业务类型、三大类指标和17个具体指标。评价的等级分为优、良、中、差四个等级。     

稠油降黏集输方法综述

综述了几种常用降黏集输方法（包括加热降黏、乳化降黏、低黏液环输送和掺稀输送等）的降黏原理及优缺点,并介绍了各方法的发展情况及应用现状。针对稀释降黏法,利用液化石油气（LPG）替代部分重稀释剂的稠油降黏方法更经济有效。通过对几种降黏输送方法的综合比较,认为采用化学降黏方法在稠油降黏中具有一定的优势,最后指出研制多元复配型高效降黏剂,研制高效（既降凝又降黏）的降凝降黏剂及利用各种方法的复合技术进行降黏将是稠油降黏技术的主要发展方向。     

Vehicular Ad-Hoc Networks sampling protocols for traffic monitoring and incident detection in Intelligent Transportation Systems

Vehicular Ad-Hoc Networks (VANETs) are an emerging technology soon to be brought to everyday life. Many Intelligent Transport Systems (ITS) services that are nowadays performed with expensive infrastructure, like reliable traffic monitoring and car accident detection, can be enhanced and even entirely provided through this technology. In this paper, we propose and assess how to use VANETs for collecting vehicular traffic measurements. We provide two VANET sampling protocols, named SAME and TOME, and we design and implement an application for one of them, to perform real time incident detection. The proposed framework is validated through simulations of both vehicular micro-mobility and communications on the 68 km highway that surrounds Rome, Italy. Vehicular traffic is generated based on a large real GPS traces set measured on the same highway, involving about ten thousand vehicles over many days. We show that the sampling monitoring protocol, SAME, collects data in few seconds with relative errors less than 10%, whereas the exhaustive protocol TOME allows almost fully accurate estimates within few tens of seconds. We also investigate the effect of a limited deployment of the VANET technology on board of vehicles. Both traffic monitoring and incident detection are shown to still be feasible with just 50% of equipped vehicles.     

Robust network sensor location for complete link flow observability under uncertainty

The link observability problem is to identify the minimum set of links to be installed with sensors that allow the full determination of flows on all the unobserved links. Inevitably, the observed link flows are subject to measurement errors, which will accumulate and propagate in the inference of the unobserved link flows, leading to uncertainty in the inference process. In this paper, we develop a robust network sensor location model for complete link flow observability, while considering the propagation of measurement errors in the link flow inference. Our model development relies on two observations: (1) multiple sensor location schemes exist for the complete inference of the unobserved link flows, and different schemes can have different accumulated variances of the inferred flows as propagated from the measurement errors. (2) Fewer unobserved links involved in the nodal flow conservation equations will have a lower chance of accumulating measurement errors, and hence a lower uncertainty in the inferred link flows. These observations motivate a new way to formulate the sensor location problem. Mathematically, we formulate the problem as min–max and min–sum binary integer linear programs. The objective function minimizes the largest or cumulative number of unobserved links connected to each node, which reduces the chance of incurring higher variances in the inference process. Computationally, the resultant binary integer linear program permits the use of a number of commercial software packages for its globally optimal solution. Furthermore, considering the non-uniqueness of the minimum set of observed links for complete link flow observability, the optimization programs also consider a secondary criterion for selecting the sensor location scheme with the minimum accumulated uncertainty of the complete link flow inference.     

Robust control of traffic networks under uncertain conditions

Uncertainty of traffic network operations has been a subject of lively debate in the last decade. However, little effort has been put in developing control frameworks that are not only aimed at improving the average performance of the system, but also at improving the system robustness and reliability. In fact, it can be argued that most of the current control approaches are only aimed at improving the efficiency, which can even be counterproductive from a robustness point of view. The main contributions of this article is the proposition of a new control framework based on the notion of controlled Markov processes, which explicitly takes into account the uncertainty in predicted traffic conditions and system performance. Furthermore, in contrast to traditional optimal control approaches, the objective function can include general statistic of the random system performance, such as the mean, standard deviation or 95‐percentile. The contribution aims to make clear how different performance function specifications yield different control strategies. This is shown for a relatively simple case study.     

“一带一路”框架下的南宁区域交通发展策略研究

"一带一路"倡议推动世界经贸格局走向环印度洋时代,中国贸易格局发展巨大变化,组织模式转向"枢纽-网络"结构,为南宁发展带来难得机遇。首先,基于规划和交通视角,分析历史演变、新兴趋势和南宁机遇,重新识别了南宁枢纽在航空物流中心、跨境电商分拨中心、联动珠三角与东盟之间的专业化功能组织平台、北部湾航运中心核心区等方面的战略价值,凸显枢纽独特性和相对优势。然后,梳理南宁区域交通的发展现状和面临挑战,对照目标明确短板。最后,提出"空港引领、区域联动、海陆一体"的区域交通发展策略,支撑南宁构建面向东盟的综合门户枢纽。     

运输结构调整政策下铁路货运市场的拓展空间和供给侧建议

调整运输结构,提高铁路货运比重是我国当前综合运输发展的重要政策,而探明铁路货运市场的拓展空间并有针对性地开展供给侧改革是落实该政策的必要工作。本文基于我国关于运输结构调整的相关政策及铁路货运行业的发展现状分析了我国铁路货运市场的拓展空间,指出了铁路货运增量的重点当前主要在大宗黑货而未来主要在白货的发展趋势。随后阐述了铁路在中长途白货运输市场的核心竞争力并提出了旨在充分发挥该竞争力的供给侧改革建议,包括集装箱+固定车底行车运输组织模式创新,南北向铁路通道统筹"黑白"分工以及整合神华铁路通道等。     

基于遗传算法的天然气集输管网参数优化设计

以管道建设总费用为目标建立目标函数 ,以管道的稳态分析、各节点的流量、压力及管道压力限制等为约束条件 ,建立了天然气集输管网的参数优化设计模型。该模型属非线性离散化最优组合问题 ,采用遗传方法求解 ,并给出了计算机软件算法     

城镇化视角的国外低碳交通发展经验研究

中国城镇化发展进入快速增长期,面临着巨大的资源和环境压力,交通运输作为基础性、服务性行业发挥着支撑和引导作用,迫切要求在新型城镇化进程中走低碳交通运输发展之路。发达国家在上世纪70年代基本完成了城镇化快速发展,积累了丰富的低碳交通发展经验,为我国新型城镇化快速发展阶段的低碳交通运输发展提供了重要的经验借鉴。本文结合世界各国经济发展水平和交通碳排放数据研究提出四类经济与交通发展模式,分析了各国城镇化与机动化发展特征,研究分析了国外典型国家不同空间层次上的低碳交通运输发展模式特征。从运输结构优化、公交优先发展、管理政策等角度提出了国外在城镇化背景下低碳交通运输发展的经验启示与政策建议。     

互联互通背景下广西交通外事工作的几点思考

文章依托中国与东盟加强互联互通合作的大背景,对广西交通系统的外事工作现状及问题进行了分析,探讨广西交通系统在互联互通大背景下加强外事工作的方式和对策.     

弹性需求下的轨道交通客流分配模型和算法研究

文章分析了轨道交通客流需求量的影响因素,以拥挤条件下的出行阻抗函数为基础,通过引入弹性需求条件下的轨道交通均衡配流条件,构建了弹性需求的均衡配流模型。根据模型的特点,给出了改进的用于求解弹性需求下的轨道交通均衡配流模型的Frank-wolfe算法。最后通过一个算例说明了算法的有效性和合理性。     

推动新型城镇化下的市郊铁路发展

文章认为新型城镇化下,需要发展市郊铁路推动中小城市建设,疏解中心城功能,并支撑郊区人口增长。但目前市郊铁路发展面临内涵不能适应都市圈发展的要求、缺乏合理的技术设计和标准、投资和运营压力巨大、城市政府不重视等问题。未来需要多举措有效发挥市郊铁路优化城镇规模结构的作用,降低市郊铁路建设成本,增强市郊铁路的投资回报预期,加大政府支持力度,积极吸引社会资本等。     

交通公示语误译的原因分析及对策

作为城市形象的重要表现部分,交通公示语在居民生活中占据着极其重要的地位,对于居民生活有着广泛的影响。而伴随着国家改革进程逐步深化,前往中国的外国朋友数量不断增加,在学习、旅游、工作方面外国人数量都呈现出一个快速的增长趋势,这一情况不断地在推进中国国际化进程。为了给更多的外国朋友带去便利,很多城市在制定交通公示语时都开始使用中英双语。本文分析了我国城市交通公示语误译的原因,提出了交通公示语误译的解决对策。     

碳达峰目标下道路运输行业低碳发展路径思考与建议

本文在当前实现道路运输碳达峰目标背景下,分析了道路运输行业碳排放的特点,总结了实现道路运输行业碳达峰目标的关键点和存在的问题,结合道路运输节能低碳技术的研发和应用,提出了道路运输行业实现碳达峰目标的发展路径,并在此基础上进一步形成了推动道路运输行业碳达峰的具体建议,为道路运输行业低碳发展提供了借鉴和参考.     

Integrated airline planning: Robust update of scheduling and fleet balancing under demand uncertainty

The airline schedule planning problem is defined as the sequence of decisions that need to be made to obtain a fully operational flight schedule. Historically, the airline scheduling problem has been sequentially solved. However, there have already been many attempts in order to obtain airline schedules in an integrated way. But due to tractability issues it is nowadays impossible to determine a fully operative and optimal schedule with an integrated model which accounts for all the key airline related aspects such as competitive effects, stochastic demand figures and uncertain operating conditions. Airlines usually develop base schedules, which are obtained much time in advance to the day of operations and not accounting for all the related uncertainty. This paper proposes a mathematical model in order to update base schedules in terms of timetable and fleet assignments while considering stochastic demand figures and uncertain operating conditions, and where robust itineraries are introduced in order to ameliorate miss-connected passengers. The proposed model leads to a large-scale problem which is difficult to be solved. Therefore, a novel improved and accelerated Benders decomposition approach is proposed. The analytical work is supported with case studies involving the Spanish legacy airline, IBERIA. The presented approach shows that the number of miss-connected passengers may be reduced when robust planning is applied.     

Robust identification of air traffic flow patterns in Metroplex terminal areas under demand uncertainty

Multi-Airport Systems (MAS), or Metroplexes, serve air traffic demand in cities with two or more airports. Due to the spatial proximity and operational interdependency of the airports, Metroplex airspaces are characterized by high complexity, and current system structures fail to provide satisfactory utilization of the available airspace resources. In order to support system-level design and management towards increased operational efficiency in such systems, an accurate depiction of major demand patterns is a prerequisite. This paper proposes a framework for the robust identification of significant air traffic flow patterns in Metroplex systems, which is aligned with the dynamic route service policy for the effective management of Metroplex operations. We first characterize deterministic demand through a spatio-temporal clustering algorithm that takes into account changes in the traffic flows over the planning horizon. Then, in order to handle uncertainties in the demand, a Distributionally Robust Optimization (DRO) approach is proposed, which takes into account demand variations and prediction errors in a robust way to ensure the reliability of the demand identification. The DRO-based approach is applied on pre-tactical (i.e. one-day planning) as well as operational levels (i.e. 2-h rolling horizon). The framework is applied to Time Based Flow Management (TBFM) data from the New York Metroplex. The framework and results are validated by Subject Matter Experts (SMEs).